Object knowledge is hierarchical. For example, a Labrador belongs to the category of dogs, all dogs are mammals, and all mammals are animals. Several hypotheses have been proposed about how this hierarchical property of object representations might be reflected in the spatial organization of ventral visual cortex. For example, all exemplars of a basic-level category might activate the same feature columns or cortical patches (e.g., Tanaka, 2003, Cerebral Cortex), so that a differentiation between specific exemplars is only possible by comparing the responses of neurons within these columns or patches. According to this view, category selectivity would be organized at a larger spatial scale compared to exemplar selectivity. Little empirical evidence is available for such proposals from monkey studies, and no direct evidence from experiments with human subjects. Here we describe a new method in which we use fMRI data to infer differences between stimulus properties in the scale at which they are organized. The method is based on the reasoning that spatial smoothing of fMRI data will have a larger beneficial effect for a larger-scale functional organization. We applied this method to several datasets, including an experiment in which basic-level category selectivity (e.g., face versus building) was compared with subordinate-level selectivity (e.g., rural building versus skyscraper). The results reveal a significantly larger beneficial effect of smoothing for basic-level selectivity compared to subordinate-level selectivity. This is in line with the proposal that selectivity for stimulus properties that underlie finer distinctions between objects is organized at a finer scale than selectivity for stimulus properties that differentiate basic-level categories. This finding confirms the existence of multiple scales of organization in ventral visual cortex.